Grassland vegetation recovery target identification method based on multi-index comprehensive determination

Abstract

The invention discloses a grassland recovery target identification method based on multi-index comprehensive determination, and the method comprises the steps: firstly carrying out data collection, and collecting community structure feature data, key function character data and root depth index data in a target land parcel in the middle and last ten days of July; secondly, the species dominance degree, the functional diversity and the community stability are calculated according to the data collected in the first step; and finally, threshold judgment is carried out through calculated data, namely, whether the target plot needs to be recovered and a specific recovery mode are judged according to an index calculation result. According to the technical scheme, a quantitative judgment standard easy to operate is established, species recovery and community recovery are clearly distinguished through multi-index comprehensive evaluation, the grassland vegetation recovery target identification method based on multi-index comprehensive judgment is provided, the efficiency of grassland ecological restoration is improved, and high-quality development of grassland is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of grassland ecological restoration, and more particularly to a grassland restoration target identification method based on multi-index comprehensive judgment. Background Art

[0002] As one of the important terrestrial ecosystems, grassland plays a key role in maintaining ecological security and is an important barrier. Vegetation restoration is the foundation of grassland ecological restoration. Restoration targets typically focus on two types of restoration species: replenishing target species to rapidly restore grassland functions. Restoring communities, on the other hand, involves optimizing species combinations to construct target communities and maintain stable vegetation. Restoration targets vary depending on the target area. Choosing the wrong restoration target can lead to ineffective restoration and economic losses. Scientifically and effectively determining the right vegetation restoration target for degraded grasslands remains a key technical challenge in grassland ecological restoration.

[0003] Traditional methods often rely on vegetation cover or the number of a single species, which cannot fully reflect the true needs of vegetation restoration. Furthermore, due to their subjective judgment, they lack clear quantitative standards to distinguish between species restoration and community restoration. Summary of the Invention

[0004] In view of this, the present invention provides a determination method for scientifically and rationally determining which vegetation restoration method to adopt for grassland.

[0005] To achieve the above object, the present invention adopts the following technical solutions: A grassland restoration target identification method based on multi-index comprehensive judgment includes the following steps: Step 1: Data Collection In mid-to-late July, data on community structure characteristics, key functional traits, and root depth index were collected in the target plots; Step 2: Calculate indicators Calculate species dominance, functional diversity, and community stability based on the data collected in step 1; Step 3: Threshold determination Based on the indicator calculation results of step 2, determine whether the target land needs to be restored and the specific restoration method.

[0006] Furthermore, in step 1, a sample method is used for data collection, wherein: Community structure characteristic data: including the name, category and density of plant species; Key functional traits: including plant height, specific leaf area, and leaf nitrogen content for each species; Root depth index: The roots in the 0-50 cm soil layer were collected in a 10 cm layer. The WinRHIZO analysis software was used to measure the total length of the roots in each layer and calculate the root depth index.

[0007] Furthermore, the root depth index is specifically calculated as: Where: D w is the weighted average root depth, d i For the i The depth of the midpoint of the soil layer, r i For the i Root length, n is the number of sampling layers; RDI is the root depth index, D max : Maximum depth of root distribution.

[0008] Furthermore, the specific calculation method in step 2 is: Species dominance, expressed as SD, SD = (target species density / total species density) × 100%; Functional diversity, expressed as FD, using the functional richness index FR ic Characterize FD, FR ic The calculations were performed using the “FD” package of R software; The calculation principle of R software is the convex hull method (Convex Hull Volume), using 4 species and 3 traits P 1 ( x 1, y 1, z 1) to P 4 ( x 4, y 4, z 4) as an example, first perform Z-score standardization on the data, and the calculation formula is: in, m is the data mean, s is the standard deviation.

[0009] Next, calculate the volume of the convex hull V， Functional richness index FR ic in: x 1 tox 4 species P 1 to P 4 of x The standardized value of the trait, y 1 to y 4 species P 1 to P 4 of x Normalized values of traits, z1 to z 4 species P 1 to P 4 of z Normalized value of the trait.

[0010] Community stability, expressed as CS, CS = proportion of perennial plants × root depth index ( RDI ).

[0011] Furthermore, the specific judgment basis is: SD>40% and FD>2 and CS>0.3, no recovery is required; If SD < 40%, FD > 2, and CS > 0.3, vegetation restoration should be carried out using overseeding of target species; If SD < 40%, FD > 2, and CS < 0.3, vegetation restoration should be carried out by reseeding target species and applying organic fertilizer; If SD>40%, FD<2, and CS>0.3, reseeding should be carried out with a target species: other native species ratio of 1:2 to 1:3; If SD>40%, FD<2, and CS<0.3, reseeding and organic fertilizer application should be carried out at a target species: other native species ratio of 1:2-1:3 for vegetation restoration; If SD < 40%, FD < 2, and CS > 0.3, reseeding should be carried out with a target species: other native species ratio of 2:1 to 3:1; If SD < 40%, FD < 2, and CS < 0.3, vegetation restoration should be carried out by reseeding with a target species: other native species ratio of 2:1 to 3:1 and applying organic fertilizer.

[0012] Furthermore, the degree of vegetation restoration is an increase of more than 40% in the aboveground biomass of plants.

[0013] Furthermore, the organic fertilizer is a mixed compost of air-dried cow dung and straw, characterized by an organic matter content ≥35%, 20:1≤C / N≤25:1, a salt content ≤0.5%, 6.0≤pH≤7.0, an application rate of 25~35t / ha, and is applied 2~3 weeks before sowing.

[0014] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a grassland restoration target identification method based on multi-index comprehensive judgment, which has the following beneficial effects: The technical solution of the present invention establishes an easy-to-operate quantitative judgment standard, clearly distinguishes species recovery from community recovery through multi-indicator comprehensive evaluation, and provides a grassland vegetation restoration target identification method based on multi-indicator comprehensive judgment to improve the efficiency of grassland ecological restoration and promote high-quality grassland development. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0016] Figure 1 This is the experimental effect diagram of Example 1; Figure 2 This is the experimental effect diagram of Example 2. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] The method for determining whether grassland is a target species or target community for restoration includes the following steps: Step 1: Data Collection In mid-to-late July, data on community structure characteristics, key functional traits, and root depth index were collected. Community structure characteristics: Use sampling methods to investigate and record the name, type and density of each plant species in the sample plot; Key functional traits: plant height, specific leaf area, and leaf nitrogen content of each species within the quadrat were measured; Root depth index: Roots from the 0-50 cm soil layer were collected in 10 cm layers. The total length of roots in each layer was measured using WinRHIZO analysis software to calculate the root depth index. Step 2: Calculate indicators Species dominance (SD): SD = (target species density / total species density) × 100%; Functional diversity (FD): using the functional richness index FR ic Characterize FD, FR ic The calculations were performed using the “FD” package of R software; Community stability (CS): CS = proportion of perennial plants × root depth index ( RDI ), in RDI The calculation formula is as follows: Where: D w is the weighted average root depth, d i For the i The depth of the midpoint of the soil layer, r i For the i Root length, n is the number of sampling layers; RDI is the root depth index, D max : Maximum depth of root distribution; Step 3: Threshold determination 1) Determination of whether vegetation restoration is necessary: If SD>40%, FD>2, and CS>0.3, no restoration is required; otherwise, vegetation restoration is required; 2) Recovery target determination: 2.1) Criteria for species recovery: If SD < 40%, FD > 2, and CS > 0.3, vegetation restoration using overseeding of target species was selected; If SD < 40%, FD > 2, and CS < 0.3, vegetation restoration using target species reseeding and organic fertilizer application was selected; 2.2) Criteria for determining community recovery: If SD>40%, FD<2, and CS>0.3, reseeding should be carried out with a target species: other native species ratio of 1:2 to 1:3; If SD>40%, FD<2, and CS<0.3, reseeding and organic fertilizer application should be carried out at a target species: other native species ratio of 1:2-1:3 for vegetation restoration; If SD < 40%, FD < 2, and CS > 0.3, reseeding should be carried out with a target species: other native species ratio of 2:1 to 3:1; If SD < 40%, FD < 2, and CS < 0.3, reseeding with a target species: other native species ratio of 2:1-3:1 and applying organic fertilizers will be used for vegetation restoration; The degree of vegetation restoration is to increase the aboveground biomass of plants by more than 40%. The organic fertilizer is a mixed compost of air-dried cow dung and straw. The organic matter content of the organic fertilizer should be ≥35%, 20:1≤C / N≤25:1, salt content ≤0.5%, 6.0≤pH≤7.0, and the application rate should be 25-35t / ha, applied 2-3 weeks before sowing. Step 4: Dynamic Monitoring Restoration is carried out in April and May, followed by a sample survey in August each year to investigate grassland biomass, update indicator data, draw indicator change trend charts, and evaluate restoration effects.

[0019] The above solution is described below using specific embodiments.

[0020] Example 1 Degraded grassland restoration monitoring in Xing'an League, Inner Mongolia Autonomous Region 1. Data Collection (July 2022) Data collection included the name, type, and density of plant species. Plant height, specific leaf area, and leaf nitrogen content were calculated for each species. Roots were collected from the 0-50 cm soil layer in 10-cm layers. WinRHIZO analysis software was used to measure the total length of roots in each layer. The results are shown in Tables 1 and 2.

[0021] Table 1 Data of aboveground parts Table 2 Root system data

[0022] 2. Index calculation: SD: SD = (leymus density / total species density) × 100% = 184 / 311 × 100% = 59.16%; FD: The data was brought into the R software FD language package and the calculated value was 0.483; CS: Perennial plant ratio = 7 / 12 = 0.583; RDI = (44*5+83*15+28*25+12*35+6*45) / (5+15+25+35+45) / 50 = 0.457 CS=proportion of perennial plants*RDI=0.583*0.457=0.266.

[0023] 3. Judgment Results SD=59.16%(>40%), FD=0.483(<2), and CS=0.266(<0.3). Leymus chinensis and Lespedeza bicolor were sown in a ratio of 1:2-1:3 at a sowing rate of 15 kg / ha. Cow dung and straw compost (28 t / ha) were applied 16 days before sowing for vegetation restoration.

[0024] IV. Implementation Effect

[0025] Comparison of grassland biomass and various indicators before implementation and in the first and second years is shown in Figure 1 The biomass in the first and second years of implementation increased by 71.74% and 171.74% respectively, the gap between SD and the threshold of 40% narrowed by 35.70% and 69.26% respectively, the gap between FD and the threshold of 2 narrowed by 58.08% and 81.67% respectively, and the gap between CS and the threshold of 0.3 narrowed by 17.65% and 85.29% respectively.

[0026] Example 2 Monitoring of degraded grassland restoration in Baicheng City, Jilin Province 1. Data Collection (July 2022) Data collection included the name, type, and density of plant species. Plant height, specific leaf area, and leaf nitrogen content were calculated for each species. Roots were collected from the 0-50 cm soil layer in 10-cm layers. WinRHIZO analysis software was used to measure the total length of roots in each layer. The results are shown in Tables 3 and 4.

[0027] Table 3 Data of aboveground parts Table 4 Root system data

[0028] 2. Index calculation: SD: SD = (leymus density / total species density) × 100% = 86 / 253 × 100% = 33.99%; FD: The data was brought into the R software FD language package and the calculated value was 2.265; CS: Perennial plant ratio = 11 / 14 = 0.786; RDI = (37*5+52*15+33*25+21*35+10*45) / (5+15+25+35+45) / 50 = 0.476 CS=proportion of perennial plants*RDI=0.786*0.476=0.374.

[0029] 3. Judgment Results SD=33.99%(<40%), FD=2.265(>2), and CS=0.374(>0.3), and vegetation restoration was carried out by reseeding Leymus chinensis at a seeding rate of 17 kg / ha.

[0030] IV. Implementation Effect Comparison of grassland biomass and various indicators before implementation and in the first and second years is shown in Figure 2Among them, the biomass in the first and second years of implementation increased by 69.77% and 108.89% respectively, SD increased by 14.33% and 22.74% respectively, FD increased by 14.10% and 18.93% respectively, and CS increased by 9.89% and 32.35% respectively.

[0031] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other. The above description of the disclosed embodiments enables professionals and technicians in this field to implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in this field, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A grassland restoration target identification method based on multi-index comprehensive judgment, characterized by: The following steps are involved: Step 1: Data Collection In mid-to-late July, data on community structure characteristics, key functional traits, and root depth index were collected in the target plots; Step 2: Calculate indicators Calculate species dominance, functional diversity, and community stability based on the data collected in step 1; Step 3: Threshold determination Based on the indicator calculation results of step 2, determine whether the target land needs to be restored and the specific restoration method.

2. The grassland restoration target identification method based on multi-index comprehensive judgment according to claim 1 is characterized in that: In step 1, a sampling method is used for data collection, where: Community structure characteristic data: including the name, category and density of plant species; Key functional traits: including plant height, specific leaf area, and leaf nitrogen content for each species; Root depth index: The roots in the soil layer of 0-50 cm were collected in a layer of 10 cm. The total length of the roots in each layer was measured using WinRHIZO analysis software to calculate the root depth index.

3. The grassland restoration target identification method based on multi-index comprehensive judgment according to claim 2 is characterized in that: The specific calculation method in step 2 is: Species dominance, expressed as SD, SD = (target species density / total species density) × 100%; Functional diversity, expressed as FD, using the functional richness index FR ic Characterize FD, FR ic The calculations were performed using the "FD" package of R software; Community stability is expressed as CS, where CS = proportion of perennial plants × root depth index.

4. The grassland restoration target identification method based on multi-index comprehensive judgment according to claim 3 is characterized in that: The specific judgment basis is: SD>40% and FD>2 and CS>0.3, no recovery is required; If SD < 40%, FD > 2, and CS > 0.3, vegetation restoration should be carried out using overseeding of target species; If SD < 40%, FD > 2, and CS < 0.3, vegetation restoration should be carried out by reseeding target species and applying organic fertilizer; If SD>40%, FD<2, and CS>0.3, reseeding should be carried out with a target species: other native species ratio of 1:2 to 1:3; If SD>40%, FD<2, and CS<0.3, reseeding and organic fertilizer application should be carried out at a target species: other native species ratio of 1:2-1:3 for vegetation restoration; If SD < 40%, FD < 2, and CS > 0.3, reseeding should be carried out with a target species: other native species ratio of 2:1 to 3:1; If SD < 40%, FD < 2, and CS < 0.3, vegetation restoration should be carried out by reseeding with a target species: other native species ratio of 2:1 to 3:1 and applying organic fertilizer.

5. The grassland restoration target identification method based on multi-index comprehensive judgment according to claim 4 is characterized in that: The degree of vegetation restoration is an increase of more than 40% in the aboveground biomass of plants.

6. The grassland restoration target identification method based on multi-index comprehensive judgment according to claim 4 is characterized in that: The organic fertilizer is a mixed compost of air-dried cow dung and straw, characterized by an organic matter content of ≥35%, 20:1≤C / N≤25:1, a salt content of ≤0.5%, 6.0≤pH≤7.0, an application rate of 25-35t / ha, and is applied 2-3 weeks before sowing.

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